• KSII Transactions on Internet and Information Systems (TIIS)
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• v.8 no.12
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• pp.4293-4304
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• 2014

In order to ensure the wireless connectivity and seamless service to mobile users, the next generation network system will be an integration of multiple wireless access networks. In a heterogeneous wireless access system, bandwidth allocation becomes crucial for load balancing to avoid network congestion and improve system utilization efficiency. In this article, we propose a new dynamic bandwidth allocation scheme for hierarchical wireless network systems. First, we derive a multi-objective decision criterion for each access point. Second, a bargaining strategy selection algorithm is developed for the dynamic bandwidth re-allocation. Based on the intervenient Stackelberg game model, the proposed scheme effectively formulates the competitive interaction situation between several access points. The system performance of proposed scheme is evaluated by using extensive simulations. With a simulation study, it is confirmed that the proposed scheme can achieve better performance than other existing schemes under widely diverse network environments.

• International Journal of Computer Science & Network Security
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• v.22 no.4
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• pp.1-12
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• 2022

In order to overcome the power fluctuation issues in photovoltaic (PV) smart grid-connected systems and the inverter nonlinearity model problem, an adaptive backstepping command-filter and a double second order generalized Integrators (DSOGI) controller are designed in order to tune the AC current and the DC-link voltage from the DC side. Firstly, we propose to present the filter mathematical model throughout the PV system, at that juncture the backstepping control law is applied in order to control it, Moreover the command filter is bounded to the controller aiming to exclude the backstepping controller differential increase. Additionally, The adaptive law uses Lyapunov stability criterion. Its task is to estimate the uncertain parameters in the smart grid-connected inverter. A DSOGI is added to stabilize the grid currents and eliminate undesirable harmonics meanwhile feeding maximum power generated from PV to the point of common coupling (PCC). Then, guaranteeing a dynamic effective response even under very unbalanced loads and/or intermittent climate changes. Finally, the simulation results will be established using MATLAB/SIMULINK proving that the presented approach can control surely the smart grid-connected system.

• International Journal of Human Ecology
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• v.5 no.2
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• pp.61-80
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• 2004

The introduction of the Internet in homes had an effect on family systems. The purpose of this study is to investigate the changes in family systems due to Internet use in South Korea. This study classified the types of changes in the family systems and analyzes the characteristics of each type. Systems approach provides the theoretical framework for this study. First, the cluster analysis demonstrated the three types of the changes in the family subsystems due to housewives' Internet use: 'positive changes', 'negative changes', and 'no changes'. Second, there are different characteristics among the types of changes according to demographic, Internet-related, and intra-system dynamic factors. These results suggest several implications for public policy. To utilize the Internet as a useful tool to improve the quality of family life, housewives must have the ability to control the Internet use and to manage their resources. In order to enhance their abilities of using the Internet, it may be necessary for the government to provide public educational programs for housewives.

• International Journal of Fuzzy Logic and Intelligent Systems
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• v.14 no.4
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• pp.276-287
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• 2014

Neural fuzzy system (NFS) is basically a fuzzy system that has been equipped with learning capability adapted from the learning idea used in neural networks. Due to their outstanding system modeling capability, NFS have been widely employed in various applications. In this article, we intend to discuss several ideas regarding the learning of NFS for modeling systems. The first issue discussed here is about structure learning techniques. Various ideas used in the literature are introduced and discussed. The second issue is about the use of recurrent networks in NFS to model dynamic systems. The discussion about the performance of such systems will be given. It can be found that such a delay feedback can only bring one order to the system not all possible order as claimed in the literature. Finally, the mechanisms and relative learning performance of with the use of the recursive least squares (RLS) algorithm are reported and discussed. The analyses will be on the effects of interactions among rules. Two kinds of systems are considered. They are the strict rules and generalized rules and have difference variances for membership functions. With those observations in our study, several suggestions regarding the use of the RLS algorithm in NFS are presented.

• 제어로봇시스템학회:학술대회논문집
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• 2000.10a
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• pp.369-369
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• 2000

Control system by means of fuzzy theory has demonstrated its robustness in applying to the high-order and nonlinear dynamic system in that it can utilizes the human expert knowledges in system design. In this paper, first, the design methodology of HFC combined PID controller with fuzzy controller by membership function of weighting coefficient is proposed. Second, Second, an auto-tuning algorithms utilizing the simplified reasoning method and genetic algorithms is presented to improve the performance of hybrid fuzzy controller. Especially, in order to obtain the optimal scaling factors and PID parameters of HFC using GA based on advanced initial individual, three kinds of estimation modes such as basic, contraction, and expansion mode are effectively utilized. The proposed HFC is evaluated and discussed in ITAE, overshoot and rising time to show applicability and superiority with simulation results.

• 제어로봇시스템학회:학술대회논문집
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• 1993.10b
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• pp.530-533
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• 1993

This paper describes a new method of dynamic error compensation, using a digital convolution integrator and two digital low pass filters. In this method, the process of compensation consists of three steps. First, sampling and digitizing of input signal, second, removing the noise in sampled data by the low pass filter and third, making a convolution integral using the output data of low pass filters. This method showed a good experimental result of reducing dynamic error even if there was a slight noise in the input signal. As a result, the detecting time constant of resistance thermo-bulb was improved to about 1/10th.

• 제어로봇시스템학회:학술대회논문집
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• 1999.10a
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• pp.281-283
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• 1999

This topic presents an inductor short turn testing. From the rudimentary principles, the quality factor(Q) decreases due to inductor short turn. Frequency response varies because of the variation of circuit inductance and resistance. In general, short turn circuit testing is performed by comparing the ratio of an inductance and resistance of inductor in that particular circuit. An alternative method can be done by considering the response of second order circuit which can give both dynamic and static testing, whereas static testing give an error results not more than 2 turns. For dynamic testing, the result is more accurate, which can test fur the short turn number form 1 turn onward.

• 제어로봇시스템학회:학술대회논문집
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• 1990.10b
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• pp.980-984
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• 1990

In order to find the optimal control law for the precise trajectory tracking of a robot manipulator, a perturbational control method is proposed based on a linearized manipulator dynamic model which can be obtained in a very compact and computationally efficient manner using the dual number algebra. Manipulator control can be decomposed into two parts: the nominal control and the corrective perturbational control. The nominal control is precomputed from the inverse dynamic model using the quantities of a desired trajectory. The perturbational control is obtained by applying the second-variational method on the linearized dynamic model. Simulation results for a PUMA-560 robot show that, by using this controller, the desired trajectory tracking performance of the robot can be achieved, even in the presence of large initial positional disturbances.

• ETRI Journal
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• v.32 no.3
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• pp.422-429
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• 2010

We present guaranteed dynamic priority assignment schemes for multiple real-time tasks subject to (m, k)-firm deadlines. The proposed schemes have two scheduling objectives: providing a bounded probability of missing (m, k)-firm constraints and maximizing the probability of deadline satisfactions. The second scheduling objective is especially necessary in order to provide the best quality of service as well as to satisfy the minimum requirements expressed by (m, k)-firm deadlines. We analytically establish that the proposed schemes provide a guarantee on the bounded probability of missing (m, k)-firm constraints. Experimental studies validate our analytical results and confirm the effectiveness and superiority of the proposed schemes with regard to their scheduling objectives.

• Journal of the Korean Society of Safety
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• v.26 no.6
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• pp.1-6
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• 2011

This study focuses on the control strategy for industrial safety in Korea. Specifically, the effect of safety budget such as the industrial accident prevention fund on the safety performance to prevent and reduce industrial accidents is statistically examined first and modeled as a second order system. The effectiveness of such a dynamic model is also explained with a simple PI control mechanism in a feedback loop. The simulated model, however, suggests that, without improving the efficiency of the safety system, extra safety budget needed to decrease the accident rate to a level in advanced countries is far beyond the social consensus. An efficient way of reducing industrial accidents based on such a dynamic model with more internal damping but with less elastic nature in a feedback loop framework needs to be implemented.